US State-Specific Covid Update + Comparison with EU

More Continuity

State-specific data analyses for the 14 days between August 24 and September 7 largely confirm findings from prior intervals. The average death rate across all states over the last two weeks is the same as it was during mid-August. As reasserted any number of times in this series of posts, death counts are the most accurate indicator of infection. And as the state-by-state analyses have shown repeatedly, the best predictor of a state’s current death toll is its prior death toll. That’s the case again this time for predicting state-specific deaths per 100K of population: the infection rate from the preceding ten days correlates highly with current death rate (r = .79), but the correlation of deaths prior with deaths present is even higher (r = .92). Continuity prevails: high infection rates cause high death rates, and high infection rates self-perpetuate across time through contagion.

Hot Spots

There has been some change in the collection of states saddled with the ignominious title of High Outlier for test-positives and deaths.

States with test-positive rates more than 50 percent above the across-state average: Alabama, Arkansas, Georgia, Iowa, Kansas, Mississippi, Missouri, North Dakota, Oklahoma, South Dakota, Tennessee.

States with death rates more than 50 percent above average: Alabama, Arizona, Arkansas, Florida, Georgia, Louisiana, Mississippi, Nevada, South Carolina, Texas.

The southeastern states remain hot spots, as they have for most of the summer. Now though there’s a test-positive surge in the central states, extending from the western Gulf Coast north to the Canadian border. Is this fallout from last month’s annual Harley rally in Sturgis South Dakota? Is it the disproportionate cultural and financial influence of Texas — an outlier throughout the summer — through this vertical band of the country?

Comparison with the EU

Recently I ran an analysis comparing (unfavorably) the US versus Western Europe in controlling the covid pandemic. A friend suggested that I might be cherry-picking the most affluent European nations to make the US look bad. Wouldn’t it be more apt to compare the entire EU and all of its member countries with the US and its individual states? Very well: here goes.

Here’s a link to a table showing the most recent 14-day covid death rate per 100K of population of all the EU/EEA countries plus the UK. The average across those 31 countries is about 0.4 deaths per 100K. Over that same 14-day span the average US state experienced 3.0 deaths per 100K — 8 times as high as Europe. The top five Euro countries for death rates are Romania, Bulgaria, Spain, Malta, and Croatia: they averaged 1.6 deaths per 100K over the past two weeks. The ten US high-outlier states identified earlier in this post averaged 7 deaths per 100K — nearly 5 times as high as the high-outlier Euro countries. Of the 50 states + DC, only 4 — Connecticut, Maine, New Hampshire, and Vermont — had death rates as low as or lower than that of the average European country.

A Procedural Note

I’ve been doing these periodic updates primarily in order to understand the interrelationships among the corona aggregate indicators — diagnostic tests conducted, test-positive rate, percent test-positive, death rate, geography, time. And in turn I’ve used those interrelationships among measurable indicators in order to construct a fairly reliable and valid and straightforward estimate of infection rate. I think I’ve got a pretty good handle on it by now. If the US were to conduct a nationally representative random sample of diagnostic tests or antibody tests, then my understanding might change dramatically. Now it’s a matter of fine tuning what I already know. The effective contagion rate goes up and down over time, the specific states experiencing spikes gradually shift. The body count goes up and up. It might be time for me to discontinue the periodic updates, or to spread them out over longer time spans.

Is Covid Seroprevalence Underestimated?

The authors of a 3 September editorial in the British Medical Journal offer a number of reasons why covid antibody tests, which focus on detecting IgC antibodies in the blood, might underestimate the percentage of people who have been infected:

  • The test isn’t sufficiently sensitive to detect immune response to mild infection.
  • The test fails to detect immune response to recent infection/recovery.
  • IgC antibodies decline rapidly over time in recovered individuals, so the test might be administered too late to detect prior infection.
  • IgA antibodies, the primary immune response on mucosal surfaces that the coronavirus attacks, are not measured in current testing methods.
  • Saliva tests may be more sensitive than blood tests for detecting all varieties of covid antibody.

The authors don’t speculate as to the magnitude of the possible undercount. A fairly straightforward research project could throw light on the question:

  • Administer diagnostic tests to a stratified random sample of the population, or to 100 percent of some well-defined subset of the population (e.g., incoming students at a university).
  • Over subsequent weeks/months, administer antibody tests to those who came up positive on the diagnostic test.